up_model_score_specialized
Released by torchtorchkimtorch in 2026, up_model_score_specialized is an chat model. up_model_score_specialized is an open-weights chat model.
by torchtorchkimtorch
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use up_model_score_specialized in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your torchtorchkimtorch API key. osFoundry discovers up_model_score_specialized automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
up_model_score_specialized is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
up_model_score_specialized vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about up_model_score_specialized
Is up_model_score_specialized free to use?
up_model_score_specialized is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use up_model_score_specialized commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run up_model_score_specialized locally?
Yes. up_model_score_specialized is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is up_model_score_specialized best at?
up_model_score_specialized is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use up_model_score_specialized in osFoundry?
Paste your torchtorchkimtorch API key in the key dialog (or deploy the open weights for self-hostable models), assign up_model_score_specialized to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by torchtorchkimtorch on April 29, 2026. Source: https://huggingface.co/torchtorchkimtorch/up_model_score_specialized